1. Introduction to R -- 2. Research protocol for meta-analyses -- 3. Fixed-effects and random-effects in meta-analysis -- 4. Meta-analysis with binary data -- 5. Meta-analysis for continuous data -- 6. Heterogeneity in meta-analysis -- Meta-regression -- 8. Individual-patient level data analysis versus meta-analysis -- 9. Meta-analysis for rare events -- 10. Other R packages for meta-analysis.
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SUMMARY OR ABSTRACT
Text of Note
In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data a